LLMChain调用失败，返回500

[Liu-Xiaoyan97]

`template = """Answer the following questions as best you can, but speaking as a pirate might speak. You have access to the following tools:
{tools}
Use the following format:
Question: the input question you must answer
Thought: you should always think about what to do
Action: the action to take, should be one of [{tool_names}]
Action Input: the input to the action
Observation: the result of the action
... (this Thought/Action/Action Input/Observation can repeat N times)
Thought: I now know the final answer
Final Answer: the final answer to the original input question
Begin! Remember to speak as a pirate when giving your final answer. Use lots of Args
Question: {input}
{agent_scratchpad}"""

prompt = CustomPromptTemplate(
template=template,
tools_getter=get_tools,
# This omits the agent_scratchpad, tools, and tool_names variables because those are generated dynamically
# This includes the intermediate_steps variable because that is needed
input_variables=["input", "intermediate_steps"]
)

print(f""" prompt --------> {prompt.}""")

LLM chain consisting of the LLM and a prompt

llm_chain = LLMChain(llm=llm, prompt=prompt)

output_parser = CustomOutputParser()

tools = get_tools("whats the weather?")
tool_names = [tool.name for tool in tools]
agent = LLMSingleActionAgent(
llm_chain=llm_chain,
output_parser=output_parser,
stop=[" Observation:"],
allowed_tools=tool_names
)
agent_executor = AgentExecutor.from_agent_and_tools(agent=agent, tools=tools, verbose=True)
agent_executor.run("please speak loud about laugh.")`

/v1/competations
在apidoc中测试，如果不加‘stop’参数可以请求成功，但由于需要多轮对话需要stop参数，请问怎么解决？